Medical Care最新文献

{"title":"Audio-Based Health Care Collection.","authors":"","doi":"10.1097/MLR.0000000000002117","DOIUrl":"https://doi.org/10.1097/MLR.0000000000002117","url":null,"abstract":"","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":"63 2","pages":"133"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142951282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Audio-Based Care for Managing Mental Health and Substance Use Disorders in Adults: A Systematic Review.","authors":"Sheila V Patel, Lissette M Saavedra, Ivette Rodriguez Borja, Sarah Philbrick, Manny Schwimmer, Richa Ruwala, Meera Viswanathan","doi":"10.1097/MLR.0000000000002098","DOIUrl":"10.1097/MLR.0000000000002098","url":null,"abstract":"<p><strong>Background: </strong>Telehealth services can increase access to care by reducing barriers. Telephone-administered care, in particular, requires few resources and may be preferred by communities in areas that are systemically underserved. Understanding the effectiveness of audio-based care is important to combat the current mental health crisis and inform discussions related to reimbursement privileges.</p><p><strong>Objectives: </strong>We compared the effectiveness of audio-based care to usual care for managing mental health and substance use disorders (MHSUD).</p><p><strong>Design: </strong>We used systematic review methods to synthesize available evidence.</p><p><strong>Studies: </strong>We searched for English-language articles reporting randomized controlled trials (RCTs) of adults diagnosed with MHSUD published since 2012.</p><p><strong>Outcomes: </strong>We abstracted data on clinical outcomes, patient-reported health and quality of life, health care access and utilization, care quality and experience, and patient safety.</p><p><strong>Results: </strong>We included 31 RCTs of participants diagnosed with depression, post-traumatic stress disorder (PTSD), other serious mental illness (SMI), anxiety, insomnia, or substance use disorder (SUD). Most of the evidence was for interventions targeting depression, PTSD, and SUD. The evidence demonstrates promise for: (1) replacing in-person care with audio care for depression, other SMI, and SUD (very low to moderate certainty of comparable effectiveness); and (2) adding audio care to monitor or treat depression, PTSD, anxiety, insomnia, and SUD (low to moderate certainty of evidence favoring audio care for clinical outcomes).</p><p><strong>Conclusions: </strong>MHSUD can be managed with audio care in certain situations. However, more evidence is needed across conditions, and specifically for anxiety and other conditions for which no research was identified.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":"63 2","pages":"134-151"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11708990/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142951280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characteristics and Readmission Risks Following Sepsis Discharges to Home.","authors":"Sang Bin You, Jiyoun Song, Jesse Y Hsu, Kathryn H Bowles","doi":"10.1097/MLR.0000000000002091","DOIUrl":"10.1097/MLR.0000000000002091","url":null,"abstract":"<p><strong>Objective: </strong>To examine the characteristics and risk factors associated with 30-day readmissions, including the impact of home health care (HHC), among older sepsis survivors transitioning from hospital to home.</p><p><strong>Research design: </strong>Retrospective cohort study of the Medical Information Mart for Intensive Care (MIMIC)-IV data (2008-2019), using generalized estimating equations (GEE) models adjusting for patient sociodemographic and clinical characteristics.</p><p><strong>Subjects: </strong>Sepsis admission episodes with in-hospital stays, aged over 65, and discharged home with or without HHC were included.</p><p><strong>Measures: </strong>The outcome was all-cause hospital readmission within 30 days following sepsis hospitalization. Covariates, including the primary predictor (HHC vs. Home discharges), were collected during hospital stays.</p><p><strong>Results: </strong>Among 9115 sepsis admissions involving 6822 patients discharged home (66.8% HHC, 33.2% Home), HHC patients, compared with those discharged without services, were older, had more comorbidities, longer hospital stays, more prior hospitalizations, more intensive care unit admissions, and higher rates of septic shock diagnoses. Despite higher illness severity in the HHC discharges, both groups had high 30-day readmission rates (30.2% HHC, 25.2% Home). GEE analyses revealed 14% higher odds of 30-day readmission for HHC discharges after adjusting for risk factors (aOR: 1.14; 95% CI: 1.02-1.27; P=0.02).</p><p><strong>Conclusions: </strong>HHC discharges experienced higher 30-day readmission rates than those without, indicating the need for specialized care in HHC settings for sepsis survivors due to their complex health care needs. Attention to sepsis survivors, regardless of HHC receipt, is crucial given the high readmission rates in both groups. Further research is needed to optimize postacute care/interventions for older sepsis survivors.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":"63 2","pages":"89-97"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142951285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Consistency in Self-Reported Race-and-Ethnicity Over Time: Implications for Improving the Accuracy of Imputations and Making the Best Use of Self-Report.","authors":"Ann Haas, Steven C Martino, Amelia M Haviland, Megan K Beckett, Jacob W Dembosky, Joy Binion, Torrey Hill, Marc N Elliott","doi":"10.1097/MLR.0000000000002090","DOIUrl":"https://doi.org/10.1097/MLR.0000000000002090","url":null,"abstract":"<p><strong>Background: </strong>Medicare Bayesian Improved Surname and Geocoding (MBISG), which augments an imperfect race-and-ethnicity administrative variable to estimate probabilities that people would self-identify as being in each of 6 mutually exclusive racial-and-ethnic groups, performs very well for Asian American and Native Hawaiian/Pacific Islander (AA&NHPI), Black, Hispanic, and White race-and-ethnicity, somewhat less well for American Indian/Alaska Native (AI/AN), and much less well for Multiracial race-and-ethnicity.</p><p><strong>Objectives: </strong>To assess whether temporal inconsistency of self-reported race-and-ethnicity might limit improvements in approaches like MBISG.</p><p><strong>Methods: </strong>Using the Medicare Health Outcomes Survey (HOS) baseline (2013-2018) and 2-year follow-up data (2015-2020), we evaluate the consistency of self-reported race-and-ethnicity coded 2 ways: the 6 mutually exclusive MBISG categories and individual endorsements of each racial-and-ethnic group. We compare the consistency of self-reported race-and-ethnicity (HOS) to the accuracy of MBISG (using 2021 Medicare Consumer Assessment of Healthcare Providers and Systems data).</p><p><strong>Results: </strong>Concordance (C-statistic) of HOS baseline and follow-up self-reported race-and-ethnicity was 0.95-0.97 for AA&NHPI, Black, Hispanic, and White, 0.83 for AI/AN, and 0.72 for Multiracial using mutually exclusive categories (weighted concordance=0.956). Concordance of MBISG with self-report followed a similar pattern and had similar values, with somewhat lower AI/AN and Multiracial values. The concordance of individual endorsements over time was somewhat higher than for classification (weighted concordance=0.975).</p><p><strong>Conclusions: </strong>The concordance of MBISG with self-reported race-and-ethnicity appears to be limited by the consistency of self-report for some racial-and-ethnic groups when employing the 6-mutually-exclusive category approach. The use of individual endorsements can improve the consistency of self-reported data. Reconfiguring algorithms such as MBISG in this form could improve its overall performance.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":"63 2","pages":"106-110"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142951286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Audio-Based Care for Managing Diabetes in Adults: A Systematic Review.","authors":"Shivani Reddy, Graham Booth, Manny Coker-Schwimmer, Shannon Kugley, Ivette Rodriguez-Borja, Sheila V Patel, Miku Fujita, Sarah Philbrick, Richa Ruwala, Jordan A Albritton, Karen Crotty","doi":"10.1097/MLR.0000000000002096","DOIUrl":"10.1097/MLR.0000000000002096","url":null,"abstract":"<p><strong>Objectives: </strong>We compared the effectiveness of audio-based care, as a replacement or a supplement to usual care, for managing diabetes.</p><p><strong>Background: </strong>Diabetes is a chronic condition afflicting many in the United States. The impact of audio-based care on the health of individuals with diabetes is unclear, particularly for those at risk for disparities-many of whom may only be able to access telehealth services through telephone.</p><p><strong>Methods: </strong>We used systematic review methods to synthesize available evidence. We systematically searched for English-language articles from 2012 reporting randomized controlled trials of adults diagnosed with diabetes. We abstracted data on clinical outcomes (including A1c), patient-reported health and quality-of-life, health care access and utilization, care quality and experience, and patient safety.</p><p><strong>Results: </strong>Evidence for replacing in-person care with audio care was limited (n = 2), with low certainty of evidence for greater and comparable effectiveness for A1c and harms, respectively. Supplemental audio care (n = 23) had a positive effect on A1c (pooled mean difference A1c -0.20%; n = 8763; 95% CI: -0.36% to -0.04%), with moderate certainty of evidence. Stratified results indicated that audio interventions supplementing usual care performed more favorably in individuals with A1c ≤ 9%; populations not at risk of disparities; interventions with at least monthly contact; and interventions using remote monitoring tools.</p><p><strong>Conclusions: </strong>This evidence base reveals some promise for managing diabetes with audio-based care as a supplement to in-person care. Future studies could further investigate the effectiveness of audio-based care as a replacement and modify interventions to better serve individuals with poor glucose control and those at risk for disparities.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":"63 2","pages":"152-163"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11708993/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142951277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factors Associated With Psychotherapist and Psychiatrist Participation in Public Insurance: Evidence From Georgia State.","authors":"Daniel Tadmon, Yihe Nina Gao","doi":"10.1097/MLR.0000000000002099","DOIUrl":"10.1097/MLR.0000000000002099","url":null,"abstract":"<p><strong>Objectives: </strong>This study aims to evaluate rates of public insurance participation among the different psychotherapist professions as well as among psychiatrists. In addition, it seeks to assess individual and contextual factors that are associated with public insurance participation.</p><p><strong>Background: </strong>Historically, Medicaid- and Medicare-insured individuals have faced unique barriers to access to mental health professionals. Because prior literature has focused on psychiatrists, little is currently known of public insurance participation rates among psychotherapists-even though they constitute the bulk of the mental health workforce.</p><p><strong>Methods: </strong>A retrospective analysis of Medicaid and Medicare participation among a census of all Georgia psychologists, licensed clinical social workers, licensed professional counselors, marriage and family therapists, as well as psychiatrists, using their complete licensing rosters as of November 2023 (N = 21,260).</p><p><strong>Results: </strong>Findings show that 82.7% of psychotherapists did not accept any public insurance. This rate was 58.8% among psychiatrists. Among Georgia-licensed clinicians located outside of the state, likely to practice through telehealth, insurance acceptance was substantially lower than their in-state peers', suggesting that telehealth may have limited reach among publicly-insured patients. Psychotherapists' different professions, as well as factors such as urbanicity, hospital setting, practice size, and individual tenure length, were strongly associated with the likelihood of insurance participation.</p><p><strong>Conclusion: </strong>Psychotherapists' low rates of participation in public insurance programs and meaningful variation between professions underscore that policies to better Medicaid and Medicare beneficiaries' access to mental health treatment must consider psychotherapists' unique practice patterns and implement interventions informed by them.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":" ","pages":"117-122"},"PeriodicalIF":3.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11708982/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142682265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Change Over Time in Hospital Care for Medicaid Beneficiaries: Analysis of Hospitalizations from 2016-2019.","authors":"Jacqueline Xu, Jeffrey D Hodis, Kary Calderon, Paul J Chung, Robert S Nocon","doi":"10.1097/MLR.0000000000002124","DOIUrl":"https://doi.org/10.1097/MLR.0000000000002124","url":null,"abstract":"<p><strong>Background: </strong>Historically, access to high-quality care has been a central challenge for Medicaid programs. Prior single-year analyses demonstrated that Medicaid beneficiaries account for disproportionately high patient volumes at low-quality hospitals. Given major Medicaid shifts including expansion and increased managed care, we examined recent trends in low-quality hospital use for Medicaid beneficiaries.</p><p><strong>Methods: </strong>Using Healthcare Cost and Utilization Project State Inpatient Databases, we compiled adult hospital discharges from 15 states in years 2016-2019 (N=32,788,446). Hospital quality was assessed with the Agency for Healthcare Research and Quality (AHRQ) Composite Inpatient Quality Indicator, reflecting risk-adjusted mortality for prevalent conditions. We constructed a logistic regression modeling odds of discharge from a low-quality hospital (bottom 20th percentile by year), with payer-year interactions and covariates for patient demographics (sex, age, race/ethnicity, income), comorbidities, state, and hospitalization type.</p><p><strong>Results: </strong>Overall, patients with Medicaid [adjusted odds ratio (aOR)=1.11, P<0.01] or Medicare (aOR=1.03, P<0.01) were more likely to be hospitalized in low-quality hospitals, compared with private insurance (reference). The likelihood of admission to low-quality hospitals over time varied by payer. Patients insured by Medicaid were 2% less likely to be admitted to low-quality hospitals each additional year (aOR=0.98, P<0.01). Medicare-insured patients did not show significant changes longitudinally, and privately insured patients were 3% more likely to be admitted to low-quality hospitals each year (aOR=1.03, P<0.01).</p><p><strong>Conclusions: </strong>This is one of the first studies examining associations between payer and inpatient care quality over time, critical for our rapidly changing payment environment. Although Medicaid-insured patients remain more likely to be discharged from low-quality hospitals as compared with other payers, we find promising recent trends of improving hospital quality over time for Medicaid beneficiaries.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143008131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Defining and Validating Criteria to Identify Populations Who May Benefit From Home-Based Primary Care.","authors":"Maggie R Salinger, Katherine A Ornstein, Hannah Kleijwegt, Abraham A Brody, Bruce Leff, Harriet Mather, Jennifer Reckrey, Christine S Ritchie","doi":"10.1097/MLR.0000000000002085","DOIUrl":"10.1097/MLR.0000000000002085","url":null,"abstract":"<p><strong>Background: </strong>Home-based primary care (HBPC) is an important care delivery model for high-need older adults. Currently, target patient populations vary across HBPC programs, hindering expansion and large-scale evaluation.</p><p><strong>Objectives: </strong>Develop and validate criteria that identify appropriate HBPC target populations.</p><p><strong>Research design: </strong>A modified Delphi process was used to achieve expert consensus on criteria for identifying HBPC target populations. All criteria were defined and validated using linked data from Medicare claims and the National Health and Aging Trends Study (NHATS) (cohort n=21,727). Construct validation involved assessing demographics and health outcomes/expenditures for selected criteria.</p><p><strong>Subjects: </strong>Delphi panelists (n=29) represented diverse professional perspectives. Criteria were validated on community-dwelling Medicare beneficiaries (age ≥70) enrolled in NHATS.</p><p><strong>Measures: </strong>Criteria were selected via Delphi questionnaires. For construct validation, sociodemographic characteristics of Medicare beneficiaries were self-reported in NHATS, and annual health care expenditures and mortality were obtained via linked Medicare claims.</p><p><strong>Results: </strong>Panelists proposed an algorithm of criteria for HBPC target populations that included indicators for serious illness, functional impairment, and social isolation. The algorithm's Delphi-selected criteria applied to 16.8% of Medicare beneficiaries. These HBPC target populations had higher annual health care costs [Med (IQR): $10,851 (3316, 31,556) vs. $2830 (913, 9574)] and higher 12-month mortality [15% (95% CI: 14, 17) vs. 5% (95% CI: 4, 5)] compared with the total validation cohort.</p><p><strong>Conclusions: </strong>We developed and validated an algorithm to define target populations for HBPC, which suggests a need for increased HBPC availability. By enabling objective identification of unmet demands for HBPC access or resources, this algorithm can foster robust evaluation and equitable expansion of HBPC.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":" ","pages":"27-37"},"PeriodicalIF":3.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11617084/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142469508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hospital-Level Variation in COVID-19 Treatment Among Hospitalized Adults in the United States: A Retrospective Cohort Study.","authors":"G Caleb Alexander, Brian T Garibaldi, Huijun An, Kathleen M Andersen, Matthew L Robinson, Kunbo Wang, Yanxun Xu, Joshua F Betz, Albert W Wu, Arielle Fisher, Shanna A Egloff, Kenneth E Sands, Hemalkumar B Mehta","doi":"10.1097/MLR.0000000000002086","DOIUrl":"10.1097/MLR.0000000000002086","url":null,"abstract":"<p><strong>Study design: </strong>Retrospective cohort study.</p><p><strong>Objective: </strong>To characterize variation in dexamethasone and remdesivir use over time among hospitals.</p><p><strong>Background: </strong>Little is known about hospital-level variation in COVID-19 drug treatments in a large and diverse network in the United States.</p><p><strong>Methods: </strong>We selected individuals hospitalized with COVID-19 across 163 hospitals between February 23, 2020 and October 31, 2021 from using the HCA CHARGE, an electronic health record repository from a network of community health care facilities in the United States. We quantified receipt of dexamethasone, remdesivir, and combined use of dexamethasone and remdesivir during the hospital stay. We used 2-level logistic regression models to determine the intraclass correlation coefficient (ICC) at the hospital level, adjusting for patient and hospital characteristics. The ICC shows the proportion of total variation in drug use accounted for by hospitals.</p><p><strong>Results: </strong>Among 161,667 individuals hospitalized with COVID-19, 73.0% were treated with dexamethasone, 49.1% with remdesivir, and 45.0% with both dexamethasone and remdesivir. The proportion of variation in dexamethasone use was 12.7% (adjusted ICC: 0.127), 8.5% for remdesivir, and 11.3% for combined drug use, indicating low interhospital variation. In the fully adjusted models, between-facility variation in dexamethasone use declined from 34.1% in February-March 2020 to 11.3% in January-March 2021 and then increased to 17.3% in July-October 2021. The variation in remdesivir use remained relatively stable during the study period.</p><p><strong>Conclusions: </strong>During the first 2 years of the pandemic, there was relatively consistent use of dexamethasone and remdesivir across the hospitals examined. Consistent adoption and implementation of treatment guidelines across the hospitals examined may have led to a decrease in variation in drug usage over time.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":" ","pages":"9-17"},"PeriodicalIF":3.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11624058/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142469509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Plan of Care Visits: Implementation During Hospitalization and Association With 30-Day Readmissions in a Large, Integrated Health Care System.","authors":"Steven P Masiano, Susannah Rose, Judith Wolfe, Nancy M Albert, Alex Milinovich, Leslie Jurecko, Beri Ridgeway, Michael W Kattan, Anita D Misra-Hebert","doi":"10.1097/MLR.0000000000002081","DOIUrl":"10.1097/MLR.0000000000002081","url":null,"abstract":"<p><strong>Background: </strong>Plan of Care of Visits (POCV), including the patient, nurse, and hospital provider were implemented across an integrated health system to improve provider-patient communication during hospitalization and patient outcomes.</p><p><strong>Objectives: </strong>To assess POCV adoption after implementation, patient characteristics assosites were classified as teachsites were classified as teachsites were classified as teachsites were classified as ciated with POCV completion, and association of POCV with 30-day readmissions.</p><p><strong>Methods: </strong>This retrospective cohort study utilized electronic medical record (EMR) data of 237,430 adult patients discharged to home from 11 hospitals from January 2020 to December 2022. POCV completion was a discrete EMR variable. POCV adoption was estimated monthly by hospital as proportion of patients with at least 1 POCV during hospitalization, with variation among hospitals measured using the Variance Partition Coefficient (VPC). Multivariable logistic regressions assessed factors associated with POCV completion and POCV association with 30-day readmission.</p><p><strong>Results: </strong>POCV adoption increased from 69% to 94% (2020-2022) and varied by 50% across hospitals (VPC 0.50, 95% CI: 0.29-0.70). Odds of a discharge-day POCV were lower among older patients (≥65 vs. 18-34 y, OR 0.81, CI: 0.79-0.83), and higher among female (OR 1.06; CI: 1.04-1.07), Asian (vs. White, OR 1.13; CI: 1.06-1.21), Hispanic (OR 1.09; CI: 1.05-1.13), and surgical patients (vs. medical, OR 1.33; CI: 1.30-1.35). Patients completing discharge-day POCV had lower 30-day readmission odds (2022 OR 0.76, CI: 0.73-0.79). Patients with POCV on ≥75% of hospital days had similar readmission odds trends.</p><p><strong>Conclusions: </strong>POCV implementation was successful, and POCV completion was associated with fewer 30-day readmissions. Future work should focus on increasing POCV adoption while reducing hospital variation.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":" ","pages":"52-61"},"PeriodicalIF":3.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142469512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}